AWS costs can easily get out of control, especially as an application grows and teams keep adding new services. The good news is that most unnecessary spending comes from poor default decisions rather than real system requirements. In this article, we go through ten essential AWS cost hacks that every developer should know and apply in practice.
1. Right-size your EC2 instances
One of the most common reasons for high AWS bills is overprovisioned EC2 instances. Many systems don’t use a fraction of their capacity and are usually just sitting there doing nothing. By regularly monitoring CPU, memory, and other metrics, you can right-size instances to match real usage. This single change often results in savings of 20 to 40 percent without affecting performance.
2. Use Auto Scaling instead of static resources
Static servers cost money even when no one is using them. Auto Scaling allows your infrastructure to grow and shrink based on actual demand. This is especially useful for applications with daily traffic spikes or seasonal usage patterns. You only pay for what you need at any given moment.
3. Use Reserved Instances or Savings Plans for stable workloads
If a service runs continuously and has predictable usage, on-demand pricing is usually the most expensive option. Reserved Instances and Savings Plans offer significant discounts in exchange for long-term commitment. They work best for databases, core backend services, and internal systems. A small amount of planning can lead to substantial monthly savings. But be careful, if you buy them ahead of time and don’t use them, you’re still going to pay for them.
4. Use Spot Instances for batch and non-critical workloads
Spot Instances take advantage of unused AWS capacity and are therefore much cheaper than standard instances. They are ideal for batch jobs, CI pipelines, and data processing tasks. While interruptions are possible, most of these workloads can handle restarts. When designed correctly, the cost savings can be dramatic.
Don’t use them for stable production workloads
5. Shut down idle resources
This one seems obvious, but many, many people forget about idle instances, or sometimes they don’t even know about them until it’s too late.
Idle resources are silent budget killers. EC2 instances, RDS databases, and load balancers often remain running without serving any real purpose. Automating shutdowns outside of working hours is simple and highly effective. This is often the fastest way to see immediate cost reductions.
6. Move cold data to S3 Intelligent-Tiering or Glacier
Not all data needs to be instantly accessible. Data that is rarely accessed should not live in expensive storage tiers. S3 Intelligent-Tiering automatically optimizes storage costs without manual intervention. Glacier is a great option for archives and long-term backups.
7. Minimize data transfer costs
Data transfer is one of the most underestimated AWS expenses. Cross AZ traffic and outbound data can add up quickly. Keeping services within the same availability zone where possible can significantly reduce costs.
8. Use serverless where it makes sense
Serverless pricing is based on execution time rather than uptime. For event driven systems and low or unpredictable traffic workloads, this model is often far more cost effective. It also reduces operational overhead. Fewer servers mean less maintenance and fewer hidden costs.
9. Set up AWS Budgets and Cost Anomaly Detection
You cannot control what you cannot see. AWS Budgets let you define spending limits and receive alerts before costs become a problem. Cost Anomaly Detection automatically identifies unusual spikes in usage. These tools are essential for teams running production workloads.
10. Delete unused snapshots, AMIs, and EBS volumes
Storage resources tend to accumulate over time. Old snapshots, AMIs, and unused EBS volumes often provide no real value but continue to generate costs. Regular cleanup and automation can lead to consistent long-term savings. This is a small habit with a big financial impact.
Once, while doing an audit report for a company, I found around ten 2 TB snapshots lying around, scattered across random regions that no one knew about.
Conclusion
Optimizing AWS costs is not a one time task but an ongoing process. Most savings come from discipline, visibility, and smart architectural decisions. When these cost hacks are applied consistently, cloud spending becomes predictable and significantly lower, without sacrificing performance or reliability.
